Decision Support Systems for Massive Data

With the rapid development of computing and sensing technologies, such as ubiquitous wireless sensor networks, the amount of data from dissimilar sensors and social media have has been increasing at a rate beyond using traditional tools to analyze. Big data poses interesting information and requires different tools in various layers of the multi-sensor decision support system to be applicable. Conventional data fusion and sensor processing algorithms in a decision support system such as registration, association and fusion are not effective for massive datasets. In this project, we will develop big data analytic techniques based on
approximation theory and implement these algorithms on distributed computing platform for multi-sensor decision support. In particular, based on the needs of the industrial partner, we will focus on three data mining functions widely used in multi-sensor decision support system, namely, classification, association and estimation, for big data analytic research and development.

Faculty Supervisor:

Henry Leung

Student:

Partner:

Norpax Technologies Inc

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Calgary

Program: